Overview

Dataset statistics

Number of variables47
Number of observations3001
Missing cells30907
Missing cells (%)21.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory405.0 B

Variable types

Numeric12
Categorical19
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description22년09월_6270000_대구광역시_07_22_18_P_제과점영업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096630&dataSetDetailId=DDI_0000096647&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (99.2%)Imbalance
위생업태명 is highly imbalanced (99.2%)Imbalance
급수시설구분명 is highly imbalanced (59.9%)Imbalance
다중이용업소여부 is highly imbalanced (89.6%)Imbalance
인허가취소일자 has 3001 (100.0%) missing valuesMissing
폐업일자 has 983 (32.8%) missing valuesMissing
휴업시작일자 has 3001 (100.0%) missing valuesMissing
휴업종료일자 has 3001 (100.0%) missing valuesMissing
재개업일자 has 3001 (100.0%) missing valuesMissing
소재지전화 has 1276 (42.5%) missing valuesMissing
소재지면적 has 104 (3.5%) missing valuesMissing
소재지우편번호 has 33 (1.1%) missing valuesMissing
도로명전체주소 has 830 (27.7%) missing valuesMissing
도로명우편번호 has 848 (28.3%) missing valuesMissing
좌표정보(X) has 82 (2.7%) missing valuesMissing
좌표정보(Y) has 82 (2.7%) missing valuesMissing
남성종사자수 has 1370 (45.7%) missing valuesMissing
여성종사자수 has 1291 (43.0%) missing valuesMissing
건물소유구분명 has 3001 (100.0%) missing valuesMissing
전통업소지정번호 has 3001 (100.0%) missing valuesMissing
전통업소주된음식 has 3001 (100.0%) missing valuesMissing
홈페이지 has 3001 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 1175 (39.2%) zerosZeros
여성종사자수 has 1132 (37.7%) zerosZeros
시설총규모 has 143 (4.8%) zerosZeros

Reproduction

Analysis started2024-04-17 15:02:53.282662
Analysis finished2024-04-17 15:02:54.369534
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3001
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1501
Minimum1
Maximum3001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:02:54.422644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile151
Q1751
median1501
Q32251
95-th percentile2851
Maximum3001
Range3000
Interquartile range (IQR)1500

Descriptive statistics

Standard deviation866.4584
Coefficient of variation (CV)0.5772541
Kurtosis-1.2
Mean1501
Median Absolute Deviation (MAD)750
Skewness0
Sum4504501
Variance750750.17
MonotonicityStrictly increasing
2024-04-18T00:02:54.528491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2005 1
 
< 0.1%
1996 1
 
< 0.1%
1997 1
 
< 0.1%
1998 1
 
< 0.1%
1999 1
 
< 0.1%
2000 1
 
< 0.1%
2001 1
 
< 0.1%
2002 1
 
< 0.1%
2003 1
 
< 0.1%
Other values (2991) 2991
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3001 1
< 0.1%
3000 1
< 0.1%
2999 1
< 0.1%
2998 1
< 0.1%
2997 1
< 0.1%
2996 1
< 0.1%
2995 1
< 0.1%
2994 1
< 0.1%
2993 1
< 0.1%
2992 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
제과점영업
3001 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제과점영업
2nd row제과점영업
3rd row제과점영업
4th row제과점영업
5th row제과점영업

Common Values

ValueCountFrequency (%)
제과점영업 3001
100.0%

Length

2024-04-18T00:02:54.632358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:02:54.703426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 3001
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
07_22_18_P
3001 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_18_P
2nd row07_22_18_P
3rd row07_22_18_P
4th row07_22_18_P
5th row07_22_18_P

Common Values

ValueCountFrequency (%)
07_22_18_P 3001
100.0%

Length

2024-04-18T00:02:54.775107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:02:54.844720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_18_p 3001
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447074.3
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:02:54.906820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation22156.357
Coefficient of variation (CV)0.0064275831
Kurtosis-1.1442688
Mean3447074.3
Median Absolute Deviation (MAD)20000
Skewness-0.37912983
Sum1.034467 × 1010
Variance4.9090414 × 108
MonotonicityIncreasing
2024-04-18T00:02:54.991521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 591
19.7%
3460000 548
18.3%
3450000 532
17.7%
3410000 386
12.9%
3420000 346
11.5%
3430000 208
 
6.9%
3440000 195
 
6.5%
3480000 195
 
6.5%
ValueCountFrequency (%)
3410000 386
12.9%
3420000 346
11.5%
3430000 208
 
6.9%
3440000 195
 
6.5%
3450000 532
17.7%
3460000 548
18.3%
3470000 591
19.7%
3480000 195
 
6.5%
ValueCountFrequency (%)
3480000 195
 
6.5%
3470000 591
19.7%
3460000 548
18.3%
3450000 532
17.7%
3440000 195
 
6.5%
3430000 208
 
6.9%
3420000 346
11.5%
3410000 386
12.9%

관리번호
Text

UNIQUE 

Distinct3001
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-18T00:02:55.146350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters66022
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3001 ?
Unique (%)100.0%

Sample

1st row3410000-121-2022-00019
2nd row3410000-121-2022-00020
3rd row3410000-121-2017-00007
4th row3410000-121-2017-00008
5th row3410000-121-2017-00009
ValueCountFrequency (%)
3410000-121-2022-00019 1
 
< 0.1%
3460000-121-2011-00014 1
 
< 0.1%
3460000-121-2010-00019 1
 
< 0.1%
3460000-121-2012-00016 1
 
< 0.1%
3460000-121-2011-00010 1
 
< 0.1%
3460000-121-2011-00011 1
 
< 0.1%
3460000-121-2011-00013 1
 
< 0.1%
3460000-121-2011-00004 1
 
< 0.1%
3460000-121-2011-00005 1
 
< 0.1%
3460000-121-2011-00007 1
 
< 0.1%
Other values (2991) 2991
99.7%
2024-04-18T00:02:55.433276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26569
40.2%
1 9692
 
14.7%
- 9003
 
13.6%
2 7555
 
11.4%
3 3942
 
6.0%
4 3848
 
5.8%
7 1205
 
1.8%
6 1159
 
1.8%
5 1150
 
1.7%
9 1065
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57019
86.4%
Dash Punctuation 9003
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26569
46.6%
1 9692
 
17.0%
2 7555
 
13.2%
3 3942
 
6.9%
4 3848
 
6.7%
7 1205
 
2.1%
6 1159
 
2.0%
5 1150
 
2.0%
9 1065
 
1.9%
8 834
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9003
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66022
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26569
40.2%
1 9692
 
14.7%
- 9003
 
13.6%
2 7555
 
11.4%
3 3942
 
6.0%
4 3848
 
5.8%
7 1205
 
1.8%
6 1159
 
1.8%
5 1150
 
1.7%
9 1065
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66022
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26569
40.2%
1 9692
 
14.7%
- 9003
 
13.6%
2 7555
 
11.4%
3 3942
 
6.0%
4 3848
 
5.8%
7 1205
 
1.8%
6 1159
 
1.8%
5 1150
 
1.7%
9 1065
 
1.6%

인허가일자
Real number (ℝ)

Distinct2351
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20098154
Minimum19790328
Maximum20220929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:02:55.557438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790328
5-th percentile19950322
Q120040923
median20101213
Q320161215
95-th percentile20211014
Maximum20220929
Range430601
Interquartile range (IQR)120292

Descriptive statistics

Standard deviation82530.847
Coefficient of variation (CV)0.0041063895
Kurtosis0.22802676
Mean20098154
Median Absolute Deviation (MAD)60111
Skewness-0.664427
Sum6.031456 × 1010
Variance6.8113407 × 109
MonotonicityNot monotonic
2024-04-18T00:02:55.667320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161206 7
 
0.2%
19940217 7
 
0.2%
20110802 6
 
0.2%
20161212 5
 
0.2%
20110823 4
 
0.1%
20101213 4
 
0.1%
20180119 4
 
0.1%
20070912 4
 
0.1%
20100219 4
 
0.1%
20100528 4
 
0.1%
Other values (2341) 2952
98.4%
ValueCountFrequency (%)
19790328 1
< 0.1%
19800612 1
< 0.1%
19801024 1
< 0.1%
19801114 1
< 0.1%
19810114 1
< 0.1%
19810720 1
< 0.1%
19810905 1
< 0.1%
19810914 1
< 0.1%
19811007 1
< 0.1%
19811008 1
< 0.1%
ValueCountFrequency (%)
20220929 1
< 0.1%
20220922 1
< 0.1%
20220921 2
0.1%
20220920 1
< 0.1%
20220914 2
0.1%
20220913 1
< 0.1%
20220906 1
< 0.1%
20220905 2
0.1%
20220901 1
< 0.1%
20220829 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
3
2018 
1
983 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 2018
67.2%
1 983
32.8%

Length

2024-04-18T00:02:55.769770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:02:55.841254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2018
67.2%
1 983
32.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
폐업
2018 
영업/정상
983 

Length

Max length5
Median length2
Mean length2.9826724
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 2018
67.2%
영업/정상 983
32.8%

Length

2024-04-18T00:02:55.919806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:02:55.997751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2018
67.2%
영업/정상 983
32.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2
2018 
1
983 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 2018
67.2%
1 983
32.8%

Length

2024-04-18T00:02:56.077023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:02:56.150708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2018
67.2%
1 983
32.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
폐업
2018 
영업
983 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 2018
67.2%
영업 983
32.8%

Length

2024-04-18T00:02:56.226269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:02:56.302112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2018
67.2%
영업 983
32.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct1497
Distinct (%)74.2%
Missing983
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean20135272
Minimum20020319
Maximum20220929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:02:56.407419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020319
5-th percentile20051130
Q120090606
median20140320
Q320180619
95-th percentile20211126
Maximum20220929
Range200610
Interquartile range (IQR)90013.75

Descriptive statistics

Standard deviation52797.786
Coefficient of variation (CV)0.0026221541
Kurtosis-1.1898795
Mean20135272
Median Absolute Deviation (MAD)40900.5
Skewness-0.091026241
Sum4.0632979 × 1010
Variance2.7876062 × 109
MonotonicityNot monotonic
2024-04-18T00:02:56.527238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211031 10
 
0.3%
20180207 7
 
0.2%
20051111 7
 
0.2%
20130129 6
 
0.2%
20190108 6
 
0.2%
20220518 5
 
0.2%
20141231 5
 
0.2%
20220120 5
 
0.2%
20050125 5
 
0.2%
20151215 4
 
0.1%
Other values (1487) 1958
65.2%
(Missing) 983
32.8%
ValueCountFrequency (%)
20020319 1
< 0.1%
20020423 1
< 0.1%
20020611 2
0.1%
20020704 1
< 0.1%
20021017 1
< 0.1%
20030228 1
< 0.1%
20030304 2
0.1%
20030408 1
< 0.1%
20030522 1
< 0.1%
20030616 1
< 0.1%
ValueCountFrequency (%)
20220929 2
0.1%
20220927 1
< 0.1%
20220926 1
< 0.1%
20220925 2
0.1%
20220921 1
< 0.1%
20220905 1
< 0.1%
20220902 1
< 0.1%
20220829 1
< 0.1%
20220826 2
0.1%
20220817 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

소재지전화
Text

MISSING 

Distinct1614
Distinct (%)93.6%
Missing1276
Missing (%)42.5%
Memory size23.6 KiB
2024-04-18T00:02:56.834672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.729855
Min length3

Characters and Unicode

Total characters18509
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1531 ?
Unique (%)88.8%

Sample

1st row053 2560359
2nd row005302526001
3rd row053 2560453
4th row053 4310055
5th row053 2573393
ValueCountFrequency (%)
053 1369
36.5%
070 23
 
0.6%
793 11
 
0.3%
741 11
 
0.3%
2452901 10
 
0.3%
311 10
 
0.3%
639 9
 
0.2%
794 9
 
0.2%
380 9
 
0.2%
795 8
 
0.2%
Other values (1722) 2284
60.9%
2024-04-18T00:02:57.210211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2976
16.1%
0 2648
14.3%
3 2607
14.1%
2054
11.1%
2 1485
8.0%
6 1334
7.2%
7 1215
6.6%
4 1142
 
6.2%
1 1102
 
6.0%
8 1033
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16455
88.9%
Space Separator 2054
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2976
18.1%
0 2648
16.1%
3 2607
15.8%
2 1485
9.0%
6 1334
8.1%
7 1215
7.4%
4 1142
 
6.9%
1 1102
 
6.7%
8 1033
 
6.3%
9 913
 
5.5%
Space Separator
ValueCountFrequency (%)
2054
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18509
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2976
16.1%
0 2648
14.3%
3 2607
14.1%
2054
11.1%
2 1485
8.0%
6 1334
7.2%
7 1215
6.6%
4 1142
 
6.2%
1 1102
 
6.0%
8 1033
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2976
16.1%
0 2648
14.3%
3 2607
14.1%
2054
11.1%
2 1485
8.0%
6 1334
7.2%
7 1215
6.6%
4 1142
 
6.2%
1 1102
 
6.0%
8 1033
 
5.6%

소재지면적
Text

MISSING 

Distinct1877
Distinct (%)64.8%
Missing104
Missing (%)3.5%
Memory size23.6 KiB
2024-04-18T00:02:57.501252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9585778
Min length3

Characters and Unicode

Total characters14365
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1417 ?
Unique (%)48.9%

Sample

1st row40.06
2nd row53.99
3rd row2.20
4th row4.10
5th row8.90
ValueCountFrequency (%)
00 76
 
2.6%
33.00 21
 
0.7%
20.00 17
 
0.6%
3.30 15
 
0.5%
36.00 15
 
0.5%
26.40 14
 
0.5%
30.00 14
 
0.5%
40.00 12
 
0.4%
10.00 12
 
0.4%
28.00 11
 
0.4%
Other values (1867) 2690
92.9%
2024-04-18T00:02:57.886379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2897
20.2%
0 2393
16.7%
2 1434
10.0%
3 1209
8.4%
4 1152
 
8.0%
5 1019
 
7.1%
1 1014
 
7.1%
6 946
 
6.6%
8 829
 
5.8%
7 743
 
5.2%
Other values (2) 729
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11467
79.8%
Other Punctuation 2898
 
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2393
20.9%
2 1434
12.5%
3 1209
10.5%
4 1152
10.0%
5 1019
8.9%
1 1014
8.8%
6 946
 
8.2%
8 829
 
7.2%
7 743
 
6.5%
9 728
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 2897
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14365
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2897
20.2%
0 2393
16.7%
2 1434
10.0%
3 1209
8.4%
4 1152
 
8.0%
5 1019
 
7.1%
1 1014
 
7.1%
6 946
 
6.6%
8 829
 
5.8%
7 743
 
5.2%
Other values (2) 729
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14365
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2897
20.2%
0 2393
16.7%
2 1434
10.0%
3 1209
8.4%
4 1152
 
8.0%
5 1019
 
7.1%
1 1014
 
7.1%
6 946
 
6.6%
8 829
 
5.8%
7 743
 
5.2%
Other values (2) 729
 
5.1%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct509
Distinct (%)17.1%
Missing33
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean704220.5
Minimum700010
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:02:58.003164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700093
Q1702040
median704080
Q3705831.25
95-th percentile711812
Maximum711891
Range11881
Interquartile range (IQR)3791.25

Descriptive statistics

Standard deviation2756.276
Coefficient of variation (CV)0.0039139389
Kurtosis0.92461666
Mean704220.5
Median Absolute Deviation (MAD)1945
Skewness0.82152858
Sum2.0901265 × 109
Variance7597057.5
MonotonicityNot monotonic
2024-04-18T00:02:58.133867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
700082 84
 
2.8%
706170 42
 
1.4%
702886 40
 
1.3%
704834 28
 
0.9%
706803 28
 
0.9%
701020 26
 
0.9%
702040 26
 
0.9%
700092 25
 
0.8%
702845 25
 
0.8%
700718 24
 
0.8%
Other values (499) 2620
87.3%
(Missing) 33
 
1.1%
ValueCountFrequency (%)
700010 1
 
< 0.1%
700040 3
 
0.1%
700060 8
 
0.3%
700070 18
 
0.6%
700082 84
2.8%
700092 25
 
0.8%
700093 15
 
0.5%
700100 1
 
< 0.1%
700111 1
 
< 0.1%
700150 15
 
0.5%
ValueCountFrequency (%)
711891 6
 
0.2%
711874 5
 
0.2%
711873 1
 
< 0.1%
711872 1
 
< 0.1%
711864 3
 
0.1%
711863 4
 
0.1%
711862 1
 
< 0.1%
711852 21
0.7%
711845 1
 
< 0.1%
711843 2
 
0.1%
Distinct2674
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-18T00:02:58.384436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length26.600133
Min length16

Characters and Unicode

Total characters79827
Distinct characters376
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2504 ?
Unique (%)83.4%

Sample

1st row대구광역시 중구 계산동2가 0200 현대백화점 지하1층
2nd row대구광역시 중구 계산동2가 0200 현대백화점 지하1층
3rd row대구광역시 중구 삼덕동1가 0064-0001번지 지상1층
4th row대구광역시 중구 삼덕동2가 0139-0008 지상1층
5th row대구광역시 중구 계산동2가 0200번지 현대백화점 식품관
ValueCountFrequency (%)
대구광역시 3003
 
20.3%
달서구 591
 
4.0%
수성구 548
 
3.7%
북구 532
 
3.6%
중구 386
 
2.6%
동구 346
 
2.3%
서구 208
 
1.4%
1층 204
 
1.4%
달성군 195
 
1.3%
남구 195
 
1.3%
Other values (3373) 8549
57.9%
2024-04-18T00:02:58.768225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14487
18.1%
5959
 
7.5%
1 4271
 
5.4%
3669
 
4.6%
3523
 
4.4%
0 3270
 
4.1%
3091
 
3.9%
3036
 
3.8%
3016
 
3.8%
2935
 
3.7%
Other values (366) 32570
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44800
56.1%
Decimal Number 17530
 
22.0%
Space Separator 14487
 
18.1%
Dash Punctuation 2205
 
2.8%
Close Punctuation 256
 
0.3%
Open Punctuation 256
 
0.3%
Other Punctuation 147
 
0.2%
Uppercase Letter 129
 
0.2%
Math Symbol 11
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5959
 
13.3%
3669
 
8.2%
3523
 
7.9%
3091
 
6.9%
3036
 
6.8%
3016
 
6.7%
2935
 
6.6%
2241
 
5.0%
1158
 
2.6%
924
 
2.1%
Other values (327) 15248
34.0%
Uppercase Letter
ValueCountFrequency (%)
A 48
37.2%
B 21
16.3%
C 16
 
12.4%
S 7
 
5.4%
M 6
 
4.7%
K 6
 
4.7%
T 6
 
4.7%
D 4
 
3.1%
P 4
 
3.1%
R 2
 
1.6%
Other values (6) 9
 
7.0%
Decimal Number
ValueCountFrequency (%)
1 4271
24.4%
0 3270
18.7%
2 2100
12.0%
3 1470
 
8.4%
5 1261
 
7.2%
4 1234
 
7.0%
6 1104
 
6.3%
8 987
 
5.6%
7 924
 
5.3%
9 909
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 111
75.5%
. 21
 
14.3%
/ 13
 
8.8%
@ 2
 
1.4%
Math Symbol
ValueCountFrequency (%)
~ 8
72.7%
+ 2
 
18.2%
1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 5
83.3%
c 1
 
16.7%
Space Separator
ValueCountFrequency (%)
14487
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44800
56.1%
Common 34892
43.7%
Latin 135
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5959
 
13.3%
3669
 
8.2%
3523
 
7.9%
3091
 
6.9%
3036
 
6.8%
3016
 
6.7%
2935
 
6.6%
2241
 
5.0%
1158
 
2.6%
924
 
2.1%
Other values (327) 15248
34.0%
Common
ValueCountFrequency (%)
14487
41.5%
1 4271
 
12.2%
0 3270
 
9.4%
- 2205
 
6.3%
2 2100
 
6.0%
3 1470
 
4.2%
5 1261
 
3.6%
4 1234
 
3.5%
6 1104
 
3.2%
8 987
 
2.8%
Other values (11) 2503
 
7.2%
Latin
ValueCountFrequency (%)
A 48
35.6%
B 21
15.6%
C 16
 
11.9%
S 7
 
5.2%
M 6
 
4.4%
K 6
 
4.4%
T 6
 
4.4%
e 5
 
3.7%
D 4
 
3.0%
P 4
 
3.0%
Other values (8) 12
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44799
56.1%
ASCII 35026
43.9%
Arrows 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14487
41.4%
1 4271
 
12.2%
0 3270
 
9.3%
- 2205
 
6.3%
2 2100
 
6.0%
3 1470
 
4.2%
5 1261
 
3.6%
4 1234
 
3.5%
6 1104
 
3.2%
8 987
 
2.8%
Other values (28) 2637
 
7.5%
Hangul
ValueCountFrequency (%)
5959
 
13.3%
3669
 
8.2%
3523
 
7.9%
3091
 
6.9%
3036
 
6.8%
3016
 
6.7%
2935
 
6.6%
2241
 
5.0%
1158
 
2.6%
924
 
2.1%
Other values (326) 15247
34.0%
Arrows
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1991
Distinct (%)91.7%
Missing830
Missing (%)27.7%
Memory size23.6 KiB
2024-04-18T00:02:59.072236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52
Mean length31.685398
Min length20

Characters and Unicode

Total characters68789
Distinct characters402
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1918 ?
Unique (%)88.3%

Sample

1st row대구광역시 중구 달구벌대로 2077, 현대백화점 지하1층 (계산동2가)
2nd row대구광역시 중구 달구벌대로 2077, 현대백화점 지하1층 (계산동2가)
3rd row대구광역시 중구 동성로6길 76 (삼덕동1가, 지상1층)
4th row대구광역시 중구 공평로 26-9 (삼덕동2가, 지상1층)
5th row대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)
ValueCountFrequency (%)
대구광역시 2172
 
16.0%
1층 697
 
5.1%
달서구 448
 
3.3%
북구 389
 
2.9%
수성구 370
 
2.7%
중구 301
 
2.2%
동구 261
 
1.9%
달구벌대로 189
 
1.4%
달성군 153
 
1.1%
남구 140
 
1.0%
Other values (2302) 8490
62.4%
2024-04-18T00:02:59.485656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11439
 
16.6%
4690
 
6.8%
1 3389
 
4.9%
3138
 
4.6%
3103
 
4.5%
2268
 
3.3%
2231
 
3.2%
2184
 
3.2%
2158
 
3.1%
( 2156
 
3.1%
Other values (392) 32033
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39708
57.7%
Space Separator 11439
 
16.6%
Decimal Number 10870
 
15.8%
Open Punctuation 2156
 
3.1%
Close Punctuation 2156
 
3.1%
Other Punctuation 2047
 
3.0%
Dash Punctuation 256
 
0.4%
Uppercase Letter 116
 
0.2%
Lowercase Letter 24
 
< 0.1%
Math Symbol 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4690
 
11.8%
3138
 
7.9%
3103
 
7.8%
2268
 
5.7%
2231
 
5.6%
2184
 
5.5%
2158
 
5.4%
1180
 
3.0%
978
 
2.5%
906
 
2.3%
Other values (343) 16872
42.5%
Uppercase Letter
ValueCountFrequency (%)
A 35
30.2%
B 19
16.4%
C 12
 
10.3%
M 8
 
6.9%
S 7
 
6.0%
H 5
 
4.3%
K 5
 
4.3%
D 5
 
4.3%
R 3
 
2.6%
T 3
 
2.6%
Other values (8) 14
 
12.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
33.3%
c 3
 
12.5%
a 3
 
12.5%
i 2
 
8.3%
m 1
 
4.2%
d 1
 
4.2%
l 1
 
4.2%
t 1
 
4.2%
o 1
 
4.2%
w 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 3389
31.2%
2 1509
13.9%
0 1237
 
11.4%
3 981
 
9.0%
4 785
 
7.2%
5 728
 
6.7%
6 648
 
6.0%
7 648
 
6.0%
9 482
 
4.4%
8 463
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 2035
99.4%
. 9
 
0.4%
/ 3
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 14
82.4%
+ 3
 
17.6%
Space Separator
ValueCountFrequency (%)
11439
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 256
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39708
57.7%
Common 28941
42.1%
Latin 140
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4690
 
11.8%
3138
 
7.9%
3103
 
7.8%
2268
 
5.7%
2231
 
5.6%
2184
 
5.5%
2158
 
5.4%
1180
 
3.0%
978
 
2.5%
906
 
2.3%
Other values (343) 16872
42.5%
Latin
ValueCountFrequency (%)
A 35
25.0%
B 19
13.6%
C 12
 
8.6%
e 8
 
5.7%
M 8
 
5.7%
S 7
 
5.0%
H 5
 
3.6%
K 5
 
3.6%
D 5
 
3.6%
c 3
 
2.1%
Other values (20) 33
23.6%
Common
ValueCountFrequency (%)
11439
39.5%
1 3389
 
11.7%
( 2156
 
7.4%
) 2156
 
7.4%
, 2035
 
7.0%
2 1509
 
5.2%
0 1237
 
4.3%
3 981
 
3.4%
4 785
 
2.7%
5 728
 
2.5%
Other values (9) 2526
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39708
57.7%
ASCII 29081
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11439
39.3%
1 3389
 
11.7%
( 2156
 
7.4%
) 2156
 
7.4%
, 2035
 
7.0%
2 1509
 
5.2%
0 1237
 
4.3%
3 981
 
3.4%
4 785
 
2.7%
5 728
 
2.5%
Other values (39) 2666
 
9.2%
Hangul
ValueCountFrequency (%)
4690
 
11.8%
3138
 
7.9%
3103
 
7.8%
2268
 
5.7%
2231
 
5.6%
2184
 
5.5%
2158
 
5.4%
1180
 
3.0%
978
 
2.5%
906
 
2.3%
Other values (343) 16872
42.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct776
Distinct (%)36.0%
Missing848
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean42062.255
Minimum41002
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:02:59.816791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41136.6
Q141559
median42017
Q342625
95-th percentile42927
Maximum43024
Range2022
Interquartile range (IQR)1066

Descriptive statistics

Standard deviation569.38273
Coefficient of variation (CV)0.013536667
Kurtosis-1.13763
Mean42062.255
Median Absolute Deviation (MAD)498
Skewness-0.046790241
Sum90560035
Variance324196.7
MonotonicityNot monotonic
2024-04-18T00:02:59.929298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41936 85
 
2.8%
41229 49
 
1.6%
41581 22
 
0.7%
41953 21
 
0.7%
41423 18
 
0.6%
41938 17
 
0.6%
41942 17
 
0.6%
41515 14
 
0.5%
41422 13
 
0.4%
42760 13
 
0.4%
Other values (766) 1884
62.8%
(Missing) 848
28.3%
ValueCountFrequency (%)
41002 3
0.1%
41003 2
 
0.1%
41005 3
0.1%
41007 2
 
0.1%
41009 1
 
< 0.1%
41020 1
 
< 0.1%
41026 7
0.2%
41027 1
 
< 0.1%
41029 1
 
< 0.1%
41030 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43018 11
0.4%
43017 5
0.2%
43014 5
0.2%
43009 2
 
0.1%
43008 3
 
0.1%
43005 2
 
0.1%
43004 1
 
< 0.1%
43003 3
 
0.1%
42999 1
 
< 0.1%
Distinct2365
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-04-18T00:03:00.184119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31
Mean length7.4855048
Min length1

Characters and Unicode

Total characters22464
Distinct characters684
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2062 ?
Unique (%)68.7%

Sample

1st row보정당앞산
2nd row북성로공구빵
3rd row노엘641
4th row딜리저트
5th row딜리저트
ValueCountFrequency (%)
파리바게뜨 81
 
2.2%
베이커리 64
 
1.8%
뚜레쥬르 55
 
1.5%
마들렌베이커리 23
 
0.6%
크라운베이커리 22
 
0.6%
반월당고로케 20
 
0.6%
빵굽는마을 17
 
0.5%
뉴욕베이커리 17
 
0.5%
대백베이커리 17
 
0.5%
던킨도너츠 13
 
0.4%
Other values (2481) 3275
90.9%
2024-04-18T00:03:00.647136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1172
 
5.2%
984
 
4.4%
922
 
4.1%
763
 
3.4%
714
 
3.2%
604
 
2.7%
415
 
1.8%
) 383
 
1.7%
( 382
 
1.7%
379
 
1.7%
Other values (674) 15746
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19722
87.8%
Lowercase Letter 625
 
2.8%
Space Separator 604
 
2.7%
Uppercase Letter 542
 
2.4%
Close Punctuation 383
 
1.7%
Open Punctuation 382
 
1.7%
Decimal Number 168
 
0.7%
Other Punctuation 30
 
0.1%
Dash Punctuation 6
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1172
 
5.9%
984
 
5.0%
922
 
4.7%
763
 
3.9%
714
 
3.6%
415
 
2.1%
379
 
1.9%
339
 
1.7%
326
 
1.7%
296
 
1.5%
Other values (604) 13412
68.0%
Lowercase Letter
ValueCountFrequency (%)
e 91
14.6%
a 68
 
10.9%
o 63
 
10.1%
n 42
 
6.7%
i 41
 
6.6%
r 37
 
5.9%
k 31
 
5.0%
c 28
 
4.5%
s 27
 
4.3%
t 26
 
4.2%
Other values (15) 171
27.4%
Uppercase Letter
ValueCountFrequency (%)
E 53
 
9.8%
B 50
 
9.2%
A 46
 
8.5%
K 43
 
7.9%
R 41
 
7.6%
O 40
 
7.4%
M 29
 
5.4%
N 28
 
5.2%
T 25
 
4.6%
C 25
 
4.6%
Other values (14) 162
29.9%
Decimal Number
ValueCountFrequency (%)
2 46
27.4%
1 36
21.4%
3 21
12.5%
0 16
 
9.5%
5 13
 
7.7%
6 9
 
5.4%
9 9
 
5.4%
7 7
 
4.2%
8 6
 
3.6%
4 5
 
3.0%
Other Punctuation
ValueCountFrequency (%)
& 10
33.3%
. 9
30.0%
, 5
16.7%
: 3
 
10.0%
' 3
 
10.0%
Space Separator
ValueCountFrequency (%)
604
100.0%
Close Punctuation
ValueCountFrequency (%)
) 383
100.0%
Open Punctuation
ValueCountFrequency (%)
( 382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19714
87.8%
Common 1574
 
7.0%
Latin 1168
 
5.2%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1172
 
5.9%
984
 
5.0%
922
 
4.7%
763
 
3.9%
714
 
3.6%
415
 
2.1%
379
 
1.9%
339
 
1.7%
326
 
1.7%
296
 
1.5%
Other values (597) 13404
68.0%
Latin
ValueCountFrequency (%)
e 91
 
7.8%
a 68
 
5.8%
o 63
 
5.4%
E 53
 
4.5%
B 50
 
4.3%
A 46
 
3.9%
K 43
 
3.7%
n 42
 
3.6%
R 41
 
3.5%
i 41
 
3.5%
Other values (40) 630
53.9%
Common
ValueCountFrequency (%)
604
38.4%
) 383
24.3%
( 382
24.3%
2 46
 
2.9%
1 36
 
2.3%
3 21
 
1.3%
0 16
 
1.0%
5 13
 
0.8%
& 10
 
0.6%
. 9
 
0.6%
Other values (10) 54
 
3.4%
Han
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19714
87.8%
ASCII 2741
 
12.2%
CJK 6
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1172
 
5.9%
984
 
5.0%
922
 
4.7%
763
 
3.9%
714
 
3.6%
415
 
2.1%
379
 
1.9%
339
 
1.7%
326
 
1.7%
296
 
1.5%
Other values (597) 13404
68.0%
ASCII
ValueCountFrequency (%)
604
22.0%
) 383
14.0%
( 382
 
13.9%
e 91
 
3.3%
a 68
 
2.5%
o 63
 
2.3%
E 53
 
1.9%
B 50
 
1.8%
2 46
 
1.7%
A 46
 
1.7%
Other values (59) 955
34.8%
CJK Compat Ideographs
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Number Forms
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct2761
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0141964 × 1013
Minimum2.001081 × 1013
Maximum2.022093 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:03:00.945586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001081 × 1013
5-th percentile2.0020925 × 1013
Q12.009073 × 1013
median2.0160513 × 1013
Q32.0200723 × 1013
95-th percentile2.0220506 × 1013
Maximum2.022093 × 1013
Range2.1012004 × 1011
Interquartile range (IQR)1.0999307 × 1011

Descriptive statistics

Standard deviation6.5160888 × 1010
Coefficient of variation (CV)0.0032350811
Kurtosis-1.0416972
Mean2.0141964 × 1013
Median Absolute Deviation (MAD)4.9894032 × 1010
Skewness-0.51499379
Sum6.0446035 × 1016
Variance4.2459413 × 1021
MonotonicityNot monotonic
2024-04-18T00:03:01.245485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041008000000 21
 
0.7%
20020919000000 19
 
0.6%
20021024000000 13
 
0.4%
20020916000000 13
 
0.4%
20211101041509 10
 
0.3%
20020918000000 9
 
0.3%
20021101000000 8
 
0.3%
20020830000000 6
 
0.2%
20021209000000 6
 
0.2%
20020412000000 5
 
0.2%
Other values (2751) 2891
96.3%
ValueCountFrequency (%)
20010810000000 2
0.1%
20010811000000 2
0.1%
20010816000000 1
< 0.1%
20010817000000 2
0.1%
20011030000000 1
< 0.1%
20011031000000 2
0.1%
20011101000000 1
< 0.1%
20011102000000 1
< 0.1%
20011105000000 2
0.1%
20011107000000 1
< 0.1%
ValueCountFrequency (%)
20220930041509 2
0.1%
20220929111443 1
< 0.1%
20220928161920 1
< 0.1%
20220927154923 1
< 0.1%
20220927105635 1
< 0.1%
20220927084510 1
< 0.1%
20220926154236 1
< 0.1%
20220926144736 1
< 0.1%
20220926041509 2
0.1%
20220922151656 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
I
1942 
U
1059 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowU
3rd rowI
4th rowU
5th rowI

Common Values

ValueCountFrequency (%)
I 1942
64.7%
U 1059
35.3%

Length

2024-04-18T00:03:01.446826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:01.538620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1942
64.7%
u 1059
35.3%
Distinct681
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
Minimum2018-08-31 23:59:59
Maximum2022-10-02 02:40:00
2024-04-18T00:03:01.637157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:03:01.768555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
제과점영업
2999 
푸드트럭
 
2

Length

Max length5
Median length5
Mean length4.9993336
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제과점영업
2nd row제과점영업
3rd row제과점영업
4th row제과점영업
5th row제과점영업

Common Values

ValueCountFrequency (%)
제과점영업 2999
99.9%
푸드트럭 2
 
0.1%

Length

2024-04-18T00:03:01.906569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:01.998386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2999
99.9%
푸드트럭 2
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2079
Distinct (%)71.2%
Missing82
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean343103.35
Minimum327860.09
Maximum358046.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:03:02.090358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327860.09
5-th percentile334635.58
Q1339587.5
median343588.74
Q3346200.74
95-th percentile353524.61
Maximum358046.4
Range30186.309
Interquartile range (IQR)6613.2416

Descriptive statistics

Standard deviation5194.0942
Coefficient of variation (CV)0.01513857
Kurtosis0.27628327
Mean343103.35
Median Absolute Deviation (MAD)3448.5064
Skewness0.094637971
Sum1.0015187 × 109
Variance26978614
MonotonicityNot monotonic
2024-04-18T00:03:02.202268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343588.735555 81
 
2.7%
345032.238221 42
 
1.4%
344047.164924 28
 
0.9%
347037.24197 25
 
0.8%
344047.979265 17
 
0.6%
340320.72271 13
 
0.4%
347008.880529 12
 
0.4%
339047.793379 12
 
0.4%
343705.561002 12
 
0.4%
347060.417753 10
 
0.3%
Other values (2069) 2667
88.9%
(Missing) 82
 
2.7%
ValueCountFrequency (%)
327860.094827 1
< 0.1%
327994.771471 1
< 0.1%
328015.993727 1
< 0.1%
328158.321294 1
< 0.1%
328209.625282 1
< 0.1%
328226.964839 1
< 0.1%
329898.834237 1
< 0.1%
329914.0 1
< 0.1%
330013.035782 1
< 0.1%
330084.748297 1
< 0.1%
ValueCountFrequency (%)
358046.403776 1
< 0.1%
357908.12325 1
< 0.1%
357881.329153 1
< 0.1%
356437.578421 1
< 0.1%
356425.755845 1
< 0.1%
356353.91544 2
0.1%
356351.120591 1
< 0.1%
356312.340344 1
< 0.1%
356222.826617 1
< 0.1%
356202.878304 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2078
Distinct (%)71.2%
Missing82
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean263313.43
Minimum240452.6
Maximum277860.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:03:02.335069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240452.6
5-th percentile257448.13
Q1261193.21
median263381.75
Q3265319.91
95-th percentile271412.22
Maximum277860.93
Range37408.331
Interquartile range (IQR)4126.7008

Descriptive statistics

Standard deviation4439.3531
Coefficient of variation (CV)0.016859577
Kurtosis4.296574
Mean263313.43
Median Absolute Deviation (MAD)2025.6536
Skewness-0.88336376
Sum7.6861191 × 108
Variance19707856
MonotonicityNot monotonic
2024-04-18T00:03:02.461480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
264119.01075 81
 
2.7%
262949.871621 42
 
1.4%
265132.987974 28
 
0.9%
265407.404337 25
 
0.8%
264405.128696 17
 
0.6%
272735.67566 13
 
0.4%
264056.630949 12
 
0.4%
258741.90218 12
 
0.4%
265530.003516 12
 
0.4%
265732.622769 10
 
0.3%
Other values (2068) 2667
88.9%
(Missing) 82
 
2.7%
ValueCountFrequency (%)
240452.59556 1
< 0.1%
240482.499847 1
< 0.1%
240483.091393 1
< 0.1%
240483.177406 1
< 0.1%
240839.348978 1
< 0.1%
240868.08825 1
< 0.1%
244475.0 1
< 0.1%
244562.0 1
< 0.1%
244624.0 2
0.1%
244625.0 1
< 0.1%
ValueCountFrequency (%)
277860.926384 1
< 0.1%
275847.996577 1
< 0.1%
274018.517122 1
< 0.1%
274001.175164 2
0.1%
273719.251935 1
< 0.1%
273712.082489 1
< 0.1%
273612.928446 1
< 0.1%
273587.706164 1
< 0.1%
273506.093893 1
< 0.1%
273495.538932 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
제과점영업
2999 
푸드트럭
 
2

Length

Max length5
Median length5
Mean length4.9993336
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제과점영업
2nd row제과점영업
3rd row제과점영업
4th row제과점영업
5th row제과점영업

Common Values

ValueCountFrequency (%)
제과점영업 2999
99.9%
푸드트럭 2
 
0.1%

Length

2024-04-18T00:03:02.576861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:02.663158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 2999
99.9%
푸드트럭 2
 
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.7%
Missing1370
Missing (%)45.7%
Infinite0
Infinite (%)0.0%
Mean0.44389945
Minimum0
Maximum17
Zeros1175
Zeros (%)39.2%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:03:02.737924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum17
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.99957562
Coefficient of variation (CV)2.2518064
Kurtosis68.208628
Mean0.44389945
Median Absolute Deviation (MAD)0
Skewness5.920621
Sum724
Variance0.99915141
MonotonicityNot monotonic
2024-04-18T00:03:02.823613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1175
39.2%
1 304
 
10.1%
2 96
 
3.2%
3 34
 
1.1%
4 13
 
0.4%
5 3
 
0.1%
7 2
 
0.1%
13 1
 
< 0.1%
6 1
 
< 0.1%
17 1
 
< 0.1%
(Missing) 1370
45.7%
ValueCountFrequency (%)
0 1175
39.2%
1 304
 
10.1%
2 96
 
3.2%
3 34
 
1.1%
4 13
 
0.4%
5 3
 
0.1%
6 1
 
< 0.1%
7 2
 
0.1%
9 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
13 1
 
< 0.1%
9 1
 
< 0.1%
7 2
 
0.1%
6 1
 
< 0.1%
5 3
 
0.1%
4 13
 
0.4%
3 34
 
1.1%
2 96
 
3.2%
1 304
10.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)0.8%
Missing1291
Missing (%)43.0%
Infinite0
Infinite (%)0.0%
Mean0.65321637
Minimum0
Maximum47
Zeros1132
Zeros (%)37.7%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:03:02.938808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum47
Range47
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6764917
Coefficient of variation (CV)2.5665182
Kurtosis351.37217
Mean0.65321637
Median Absolute Deviation (MAD)0
Skewness14.124613
Sum1117
Variance2.8106245
MonotonicityNot monotonic
2024-04-18T00:03:03.029909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 1132
37.7%
1 318
 
10.6%
2 155
 
5.2%
3 58
 
1.9%
4 16
 
0.5%
5 10
 
0.3%
6 10
 
0.3%
7 5
 
0.2%
11 1
 
< 0.1%
18 1
 
< 0.1%
Other values (4) 4
 
0.1%
(Missing) 1291
43.0%
ValueCountFrequency (%)
0 1132
37.7%
1 318
 
10.6%
2 155
 
5.2%
3 58
 
1.9%
4 16
 
0.5%
5 10
 
0.3%
6 10
 
0.3%
7 5
 
0.2%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
47 1
 
< 0.1%
18 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
7 5
 
0.2%
6 10
0.3%
5 10
0.3%
4 16
0.5%
Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
1288 
기타
880 
주택가주변
395 
아파트지역
349 
유흥업소밀집지역
 
50
Other values (3)
 
39

Length

Max length8
Median length7
Mean length3.7797401
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row기타
4th row기타
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1288
42.9%
기타 880
29.3%
주택가주변 395
 
13.2%
아파트지역 349
 
11.6%
유흥업소밀집지역 50
 
1.7%
학교정화(상대) 29
 
1.0%
학교정화(절대) 9
 
0.3%
결혼예식장주변 1
 
< 0.1%

Length

2024-04-18T00:03:03.134118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:03.256462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1288
42.9%
기타 880
29.3%
주택가주변 395
 
13.2%
아파트지역 349
 
11.6%
유흥업소밀집지역 50
 
1.7%
학교정화(상대 29
 
1.0%
학교정화(절대 9
 
0.3%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2120 
자율
643 
기타
235 
 
3

Length

Max length4
Median length4
Mean length3.4118627
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row자율
4th row자율
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2120
70.6%
자율 643
 
21.4%
기타 235
 
7.8%
3
 
0.1%

Length

2024-04-18T00:03:03.388549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:03.487926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2120
70.6%
자율 643
 
21.4%
기타 235
 
7.8%
3
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
상수도전용
2288 
<NA>
710 
전용상수도(특정시설의 자가용 수도)
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length19
Median length5
Mean length4.7767411
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row상수도전용
4th row상수도전용
5th row상수도전용

Common Values

ValueCountFrequency (%)
상수도전용 2288
76.2%
<NA> 710
 
23.7%
전용상수도(특정시설의 자가용 수도) 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-18T00:03:03.592442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:03.685470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2288
76.1%
na 710
 
23.6%
전용상수도(특정시설의 2
 
0.1%
자가용 2
 
0.1%
수도 2
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총직원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2594 
0
407 

Length

Max length4
Median length4
Mean length3.5931356
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2594
86.4%
0 407
 
13.6%

Length

2024-04-18T00:03:03.812970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:03.907979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2594
86.4%
0 407
 
13.6%

본사직원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2587 
0
414 

Length

Max length4
Median length4
Mean length3.586138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2587
86.2%
0 414
 
13.8%

Length

2024-04-18T00:03:03.993539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:04.070781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
86.2%
0 414
 
13.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2587 
0
414 

Length

Max length4
Median length4
Mean length3.586138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2587
86.2%
0 414
 
13.8%

Length

2024-04-18T00:03:04.161225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:04.247254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
86.2%
0 414
 
13.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2587 
0
414 

Length

Max length4
Median length4
Mean length3.586138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2587
86.2%
0 414
 
13.8%

Length

2024-04-18T00:03:04.357962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:04.442462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
86.2%
0 414
 
13.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2587 
0
414 

Length

Max length4
Median length4
Mean length3.586138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2587
86.2%
0 414
 
13.8%

Length

2024-04-18T00:03:04.542617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:04.645393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
86.2%
0 414
 
13.8%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

보증액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2587 
0
414 

Length

Max length4
Median length4
Mean length3.586138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2587
86.2%
0 414
 
13.8%

Length

2024-04-18T00:03:04.738227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:04.821592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
86.2%
0 414
 
13.8%

월세액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
<NA>
2587 
0
414 

Length

Max length4
Median length4
Mean length3.586138
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2587
86.2%
0 414
 
13.8%

Length

2024-04-18T00:03:04.904657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:03:04.985916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
86.2%
0 414
 
13.8%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
False
2960 
True
 
41
ValueCountFrequency (%)
False 2960
98.6%
True 41
 
1.4%
2024-04-18T00:03:05.056742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct1898
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.798297
Minimum0
Maximum1300
Zeros143
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2024-04-18T00:03:05.156185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.44
Q123.1
median35.19
Q356.4
95-th percentile116.16
Maximum1300
Range1300
Interquartile range (IQR)33.3

Descriptive statistics

Standard deviation54.040259
Coefficient of variation (CV)1.1547484
Kurtosis135.46644
Mean46.798297
Median Absolute Deviation (MAD)14.91
Skewness8.3785649
Sum140441.69
Variance2920.3495
MonotonicityNot monotonic
2024-04-18T00:03:05.269532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 143
 
4.8%
33.0 21
 
0.7%
20.0 17
 
0.6%
36.0 16
 
0.5%
3.3 15
 
0.5%
26.4 14
 
0.5%
30.0 13
 
0.4%
10.0 12
 
0.4%
40.0 12
 
0.4%
32.0 12
 
0.4%
Other values (1888) 2726
90.8%
ValueCountFrequency (%)
0.0 143
4.8%
0.9 1
 
< 0.1%
1.0 4
 
0.1%
1.2 1
 
< 0.1%
1.44 3
 
0.1%
1.5 3
 
0.1%
1.55 1
 
< 0.1%
1.6 2
 
0.1%
1.69 1
 
< 0.1%
1.92 1
 
< 0.1%
ValueCountFrequency (%)
1300.0 1
< 0.1%
787.0 1
< 0.1%
734.07 1
< 0.1%
732.0 1
< 0.1%
613.0 1
< 0.1%
504.1 1
< 0.1%
432.0 1
< 0.1%
424.58 1
< 0.1%
415.0 1
< 0.1%
401.85 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3001
Missing (%)100.0%
Memory size26.5 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01제과점영업07_22_18_P34100003410000-121-2022-0001920220609<NA>3폐업2폐업20220623<NA><NA><NA><NA><NA>700082대구광역시 중구 계산동2가 0200 현대백화점 지하1층대구광역시 중구 달구벌대로 2077, 현대백화점 지하1층 (계산동2가)41936보정당앞산20220624041510U2022-06-26 02:40:00.0제과점영업343588.735555264119.01075제과점영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
12제과점영업07_22_18_P34100003410000-121-2022-0002020220620<NA>3폐업2폐업20220623<NA><NA><NA><NA><NA>700082대구광역시 중구 계산동2가 0200 현대백화점 지하1층대구광역시 중구 달구벌대로 2077, 현대백화점 지하1층 (계산동2가)41936북성로공구빵20220624041510U2022-06-26 02:40:00.0제과점영업343588.735555264119.01075제과점영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
23제과점영업07_22_18_P34100003410000-121-2017-0000720170223<NA>3폐업2폐업20180123<NA><NA><NA><NA>40.06700411대구광역시 중구 삼덕동1가 0064-0001번지 지상1층대구광역시 중구 동성로6길 76 (삼덕동1가, 지상1층)41941노엘64120180123174421I2018-08-31 23:59:59.0제과점영업344380.704303264293.158737제과점영업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.06<NA><NA><NA>
34제과점영업07_22_18_P34100003410000-121-2017-0000820170223<NA>3폐업2폐업20211108<NA><NA><NA><NA>53.99700412대구광역시 중구 삼덕동2가 0139-0008 지상1층대구광역시 중구 공평로 26-9 (삼덕동2가, 지상1층)41940딜리저트20211108154904U2021-11-10 02:40:00.0제과점영업344483.228171264087.366866제과점영업00기타자율상수도전용00000<NA>00N53.99<NA><NA><NA>
45제과점영업07_22_18_P34100003410000-121-2017-0000920170223<NA>3폐업2폐업20171218<NA><NA><NA><NA>2.20700082대구광역시 중구 계산동2가 0200번지 현대백화점 식품관대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)41936딜리저트20171218153728I2018-08-31 23:59:59.0제과점영업343588.735555264119.01075제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N2.2<NA><NA><NA>
56제과점영업07_22_18_P34100003410000-121-2017-0001020170227<NA>3폐업2폐업20220513<NA><NA><NA><NA>4.10700082대구광역시 중구 계산동2가 0200 현대백화점 식품관대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)41936마듀현대백화점대구점20220513153819U2022-05-15 02:40:00.0제과점영업343588.735555264119.01075제과점영업00기타<NA>상수도전용00000<NA>00N4.1<NA><NA><NA>
67제과점영업07_22_18_P34100003410000-121-2017-0001120170227<NA>3폐업2폐업20190103<NA><NA><NA><NA>8.90700082대구광역시 중구 계산동2가 0200번지 현대백화점 식품관대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)41936슈엣20190103092540U2019-01-05 02:40:00.0제과점영업343588.735555264119.01075제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N8.9<NA><NA><NA>
78제과점영업07_22_18_P34100003410000-121-2017-0001220170228<NA>3폐업2폐업20170807<NA><NA><NA><NA>42.15700082대구광역시 중구 계산동2가 0200번지 현대백화점 식품관대구광역시 중구 달구벌대로 2077 (계산동2가, 현대백화점 식품관)41936파티세리몽슈슈 현대백화점대구점20170807100214I2018-08-31 23:59:59.0제과점영업343588.735555264119.01075제과점영업<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.15<NA><NA><NA>
89제과점영업07_22_18_P34100003410000-121-2007-0000620070423<NA>3폐업2폐업20170601<NA><NA><NA>053 2560359198.85700092대구광역시 중구 동성로2가 0156-0003번지 지상1,2,3층대구광역시 중구 동성로6길 10 (동성로2가)41941비알코리아(주)던킨도너츠20170601110357I2018-08-31 23:59:59.0제과점영업344064.229811264370.442947제과점영업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N198.85<NA><NA><NA>
910제과점영업07_22_18_P34100003410000-121-2007-0000720070807<NA>3폐업2폐업20071221<NA><NA><NA>00530252600111.00700210대구광역시 중구 하서동 0028번지 지상1층<NA><NA>아미고 베이커리20071126091515I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업<NA>1기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N11.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
29912992제과점영업07_22_18_P34800003480000-121-2014-0000320140630<NA>1영업/정상1영업<NA><NA><NA><NA>053 586 840781.88711815대구광역시 달성군 다사읍 죽곡리 210번지대구광역시 달성군 다사읍 죽곡1길 10, 1층 105,106호42918알벤토20140718130942I2018-08-31 23:59:59.0제과점영업332151.152125262911.528096제과점영업<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N81.88<NA><NA><NA>
29922993제과점영업07_22_18_P34800003480000-121-2016-0001120160909<NA>1영업/정상1영업<NA><NA><NA><NA>053 614 176740.13711873대구광역시 달성군 현풍면 중리 470-9번지 1층대구광역시 달성군 현풍면 테크노중앙대로5길 8, 1층43014파네디파파(pane di papa))20161220153326I2018-08-31 23:59:59.0제과점영업331651.937451245189.117708제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.13<NA><NA><NA>
29932994제과점영업07_22_18_P34800003480000-121-2014-0000520141208<NA>1영업/정상1영업<NA><NA><NA><NA>053 202 1232285.00711813대구광역시 달성군 다사읍 서재리 121-3대구광역시 달성군 다사읍 서재본길 4, 1~2층42923양과부띠끄엘20220812151928U2022-08-14 02:40:00.0제과점영업335138.716049264584.919088제과점영업00기타<NA>상수도전용00000<NA>00Y285.0<NA><NA><NA>
29942995제과점영업07_22_18_P34800003480000-121-2018-0000120180328<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.27711852대구광역시 달성군 논공읍 북리 803-302번지대구광역시 달성군 논공읍 논공로 774, 1층42979호밀빵20180425201620I2018-08-31 23:59:59.0제과점영업330430.957874248611.080445제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N61.27<NA><NA><NA>
29952996제과점영업07_22_18_P34800003480000-121-2014-0000420140731<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00711852대구광역시 달성군 논공읍 북리 833-75번지 외1필지대구광역시 달성군 논공읍 논공중앙로 12842985나이스 빵집20140731115743I2018-08-31 23:59:59.0제과점영업330992.612575248466.723517제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N30.0<NA><NA><NA>
29962997제과점영업07_22_18_P34800003480000-121-2015-0000420151104<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.00711842대구광역시 달성군 옥포면 강림리 1168번지대구광역시 달성군 옥포면 돌미로2서길 3-4, 1층42974베이커리20160330163420I2018-08-31 23:59:59.0제과점영업329898.834237254152.127229제과점영업<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N24.0<NA><NA><NA>
29972998제과점영업07_22_18_P34800003480000-121-2016-0000320160310<NA>1영업/정상1영업<NA><NA><NA><NA><NA>95.57711843대구광역시 달성군 옥포면 교항리 2919번지대구광역시 달성군 옥포면 돌미상업로 9, 1층 105,106호42974파리바게트 대구옥포점20160422110702I2018-08-31 23:59:59.0제과점영업330283.226863254512.172379제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.57<NA><NA><NA>
29982999제과점영업07_22_18_P34800003480000-121-2016-0000420160316<NA>1영업/정상1영업<NA><NA><NA><NA>053 611 828491.93<NA>대구광역시 달성군 현풍읍 중리 489-105대구광역시 달성군 현풍읍 테크노상업로 46, 1층 105호43017뚜레쥬르(현풍테크노점)20220921150109U2022-09-24 02:40:00.0제과점영업331608.0244625.0제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N91.93<NA><NA><NA>
29993000제과점영업07_22_18_P34800003480000-121-2016-0000520160510<NA>1영업/정상1영업<NA><NA><NA><NA><NA>105.69711812대구광역시 달성군 다사읍 매곡리 1526번지 1층대구광역시 달성군 다사읍 대실역북로2길 137, 1층42911우리밀 레헴20160523094705I2018-08-31 23:59:59.0제과점영업332392.456162263776.054896제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N68.5<NA><NA><NA>
30003001제과점영업07_22_18_P34800003480000-121-2016-0000620160513<NA>1영업/정상1영업<NA><NA><NA><NA>053 581 0045116.94711814대구광역시 달성군 다사읍 세천리 1557-5번지대구광역시 달성군 다사읍 세천북로8길 11, 1층42922우리밀 빵집20160523094525I2018-08-31 23:59:59.0제과점영업333466.083347265290.139921제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N116.94<NA><NA><NA>